Radiative effect differences between multi-layered and single-layer clouds derived from CERES, CALIPSO, and CloudSat data

Abstract. At CNR-IMAA, an aerosol lidar system has operated since May 2000 in the framework of EARLINET (European Aerosol Research Lidar Network), the first lidar network for tropospheric aerosol study on a continental scale. High quality multi-wavelength measurements make this system a reference point for the validation of data products provided by CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations), the first satellite-borne lidar specifically designed for aerosol and cloud study. Since 14 June 2006, dedicated measurements have been performed at CNR-IMAA in coincidence with CALIPSO overpasses. For the first time, results on 1-year comparisons between ground-based multi-wavelength Raman lidar measurements and corresponding CALIPSO lidar Level 1 profiles are presented. A methodology for the comparison is presented and discussed in detail. Night-time cases are considered to take advantage from Raman capability of the ground based lidar. Cases with the detection of cirrus clouds in CALIPSO data are separately analysed for taking into account multiple scattering effects. For cirrus cloud cases, few cases are available to draw any conclusions. For clear sky conditions, the comparison shows good performances of the CALIPSO on-board lidar: the mean relative difference between the ground-based and CALIPSO Level 1 measurements is always within its standard deviation at all altitudes, with a mean difference in the 3–8 km altitude range of (−2±12)%. At altitude ranges corresponding to the typical PBL height observed at CNR-IMAA, a mean difference of (−24±20)% is observed in CALIPSO data, probably due to the difference in the aerosol content at the location of PEARL and CALIPSO ground-track location. Finally, the mean differences are on average lower at all altitude ranges for the closest overpasses (at about 40 km) respect to the 80-km overpasses.

This article presents and assesses an algorithm that constructs 3D distributions of cloud from passive satellite imagery and collocated 2D nadir profiles of cloud properties inferred synergistically from lidar, cloud radar and imager data. It effectively widens the active–passive retrieved cross‐section (RXS) of cloud properties, thereby enabling computation of radiative fluxes and radiances that can be compared with measured values in an attempt to perform radiative closure experiments that aim to assess the RXS. For this introductory study, A‐train data were used to verify the scene‐construction algorithm and only 1D radiative transfer calculations were performed.The construction algorithm fills off‐RXS recipient pixels by computing sums of squared differences (a cost function F) between their spectral radiances and those of potential donor pixels/columns on the RXS. Of the RXS pixels with F lower than a certain value, the one with the smallest Euclidean distance to the recipient pixel is designated as the donor, and its retrieved cloud properties and other attributes such as 1D radiative heating rates are consigned to the recipient. It is shown that both the RXS itself and Moderate Resolution Imaging Spectroradiometer (MODIS) imagery can be reconstructed extremely well using just visible and thermal infrared channels. Suitable donors usually lie within 10 km of the recipient. RXSs and their associated radiative heating profiles are reconstructed best for extensive planar clouds and less reliably for broken convective clouds.Domain‐average 1D broadband radiative fluxes at the top of the atmosphere (TOA) for (21 km)2 domains constructed from MODIS, CloudSat and Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) data agree well with coincidental values derived from Clouds and the Earth's Radiant Energy System (CERES) radiances: differences between modelled and measured reflected shortwave fluxes are within ±10 W m−2 for ∼35% of the several hundred domains constructed for eight orbits. Correspondingly, for outgoing longwave radiation ∼65% are within ±10 W m−2. Copyright © 2011 Royal Meteorological Society and Crown in the right of Canada

Estimation of aerosol radiative forcing over an aged-background aerosol feature during advection and non-advection events using a ground-based data obtained from a Prede Skyradiometer observation

Active remote sensing instruments such as lidar and radar allow one to accurately detect the presence of clouds and give information on their vertical structure and phase. To better address cloud radiative impact over the Arctic area, a combined analysis based on lidar and radar ground-based and A-Train satellite measurements was carried out to evaluate the efficiency of cloud detection, as well as cloud type and vertical distribution, over the Eureka station (80°N, 86°W) between June 2006 and May 2010. Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) and CloudSat data were first compared with independent ground-based cloud measurements. Seasonal and monthly trends from independent observations were found to be similar among all datasets except when compared with the weather station observations because of the large reported fraction of ice crystals suspended in the lower troposphere in winter. Further investigations focused on satellite observations that are collocated in space and time with ground-based data. Cloud fraction occurrences from ground-based instruments correlated well with both CALIPSO operational products and combined CALIPSO–CloudSat retrievals, with a hit rate of 85%. The hit rate was only 77% for CloudSat products. The misdetections were mainly attributed to 1) undetected low-level clouds as a result of sensitivity loss and 2) missed clouds because of the distance between the satellite track and the station. The spaceborne lidar–radar synergy was found to be essential to have a complete picture of the cloud vertical profile down to 2 km. Errors are quantified and discussed.

Cloud radiative effects on surface downwelling fluxes are investigated using datasets from the Atmospheric Radiation Measurement Program (ARM) sites in the tropical western Pacific Ocean (TWP) region. The Nauru Island (Republic of Nauru) and Darwin, Australia, sites show large variability in sky cover, downwelling radiative fluxes, and surface cloud radiative effect (CRE) that is due to El Niño–Southern Oscillation (ENSO) and the Australian monsoon, respectively, whereas the Manus Island (Papua New Guinea) site shows little intraseasonal or interannual variability. At Nauru, the average shortwave (SW) surface CRE varies from −38.2 W m−2during La Niña conditions to −90.6 W m−2during El Niño conditions. The average longwave (LW) CRE ranges from 9.5 to 15.8 W m−2during La Niña and El Niño conditions, respectively. At Manus, the average SW and LW CREs vary by less than 5 and 2 W m−2, respectively, between the ENSO phases. The variability at Darwin is even larger than at Nauru, with average SW (LW) CRE ranging from −27.0 (8.6) W m−2in the dry season to −95.8 (17.0) W m−2in the wet season. Cloud radar measurements of cloud-base and cloud-top heights are used to define cloud types to examine the effect of cloud type on the surface CRE. Clouds with low bases contribute 71%–75% of the surface SW CRE and 66%–74% of the surface LW CRE at the three TWP sites, clouds with midlevel bases contribute 8%–9% of the SW CRE and 12%–14% of the LW CRE, and clouds with high bases contribute 16%–19% of the SW CRE and 15%–21% of the LW CRE.

In August 2019, a 4-km thick wildfire smoke layer was observed in the lower stratosphere over Leipzig, Germany, with a ground-based multiwavelength Raman lidar. The smoke was identified by the smoke-specific spectral dependence of the extinction-to-backscatter ratio (lidar ratio) measured with the Raman lidar. The spaceborne CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation) lidar CALIOP (Cloud–Aerosol Lidar with Orthogonal Polarization) detected the smoke and classified it as sulfate aerosol layer (originating from the Raikoke volcanic eruption). In this article, we discuss the reason for this misclassification. Two major sources for stratospheric air pollution were active in the summer of 2019 and complicated the CALIPSO aerosol typing effort. Besides intense forest fires at mid and high northern latitudes, the Raikoke volcano erupted in the Kuril Islands. We present two cases observed at Leipzig, one from July 2019 and one from August 2019. In July, pure volcanic sulfate aerosol layers were found in the lower stratosphere, while in August, wildfire smoke dominated in the height range up to 4–5 km above the local tropopause. In both cases, the CALIPSO aerosol typing scheme classified the layers as sulfate aerosol layers. The aerosol identification algorithm assumes non-spherical smoke particles in the stratosphere as consequence of fast lifting by pyrocumulonimbus convection. However, we hypothesize (based on presented simulations) that the smoke ascended as a results of self-lifting and reached the tropopause within 2–7 days after emission and finally entered the lower stratosphere as aged spherical smoke particles. These sphercial particles were then classified as liquid sulfate particles by the CALIPSO data analysis scheme. We also present a successful case of smoke identification by the CALIPSO retrieval method.

To study the relationship between Aerosol Optical Depth (AOD) and concentration of PM 2.5 （Particulate Matter) basing on CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation) data, 51 samples among the CALIPSO Level 2 aerosol profile data of local region from January to April 2014 are selected. After screening these 51 samples under the decided conditions, such as system stability and the type of the materials, the AODs of the samples are calculated. Then a linear regression model is constructed through Matlab software, in which AOD is independent variable and PM 2.5 is dependent variable. All the data are fit by the selected five functions: linear, logarithmic, exponential, power, and quadratic. Experimental results show that the value of correlation coefficient of the quadratic equation model is the best one among the functions. So it is feasible to monitor the concentration of PM 2.5 using the AOD calculated from CALIPSO Level 2 data.

Changes in land surface albedo and land surface evaporation modulate the atmospheric energy budget by changing temperatures, water vapor, clouds, snow and ice cover, and the partitioning of surface energy fluxes. Here idealized perturbations to land surface properties are imposed in a global model to understand how such forcings drive shifts in zonal mean atmospheric energy transport and zonal mean tropical precipitation. For a uniform decrease in global land albedo, the albedo forcing and a positive water vapor feedback contribute roughly equally to increased energy absorption at the top of the atmosphere (TOA), while radiative changes due to the temperature and cloud cover response provide a negative feedback and energy loss at TOA. Decreasing land albedo causes a northwards shift in the zonal mean intertropical convergence zone (ITCZ). The combined effects on ITCZ location of all atmospheric feedbacks roughly cancel for the albedo forcing; the total ITCZ shift is comparable to that predicted for the albedo forcing alone. For an imposed increase in evaporative resistance that reduces land evaporation, low cloud cover decreases in the northern mid-latitudes and more energy is absorbed at TOA there; longwave loss due to warming provides a negative feedback on the TOA energy balance and ITCZ shift. Imposed changes in land albedo and evaporative resistance modulate fundamentally different aspects of the surface energy budget. However, the pattern of TOA radiation changes due to the water vapor and air temperature responses are highly correlated for these two forcings because both forcings lead to near-surface warming.

Ice particle morphology and microphysical properties of cirrus clouds are essential for assessing radiative forcing associated with these clouds. We develop an optimal estimation‐based algorithm to infer cirrus cloud optical thickness (COT), cloud effective radius (CER), plate fraction including quasi‐horizontally oriented plates (HOPs), and the degree of surface roughness from the Cloud Aerosol Lidar with Orthogonal Polarization (CALIOP) and the Infrared Imaging Radiometer (IIR) on the Cloud Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) platform. A simple but realistic ice particle model is used, and the relevant bulk optical properties are computed using state‐of‐the‐art light‐scattering computational capabilities. Rigorous estimation of uncertainties related to surface properties, atmospheric gases, and cloud heterogeneity is performed. The results based on the present method show that COTs are quite consistent with other satellite products and CERs essentially agree with the other counterparts. A 1 month global analysis for April 2007, in which CALIPSO off‐nadir angle is 0.3°, shows that the HOP has significant temperature‐dependence and is critical to the lidar ratio when cloud temperature is warmer than −40°C. The lidar ratio is calculated from the bulk optical properties based on the inferred parameters, showing robust temperature dependence. The median lidar ratio of cirrus clouds is 27–31 sr over the globe.

Impact of CALIPSO profile data assimilation on 3-D aerosol improvement in a size-resolved aerosol model

Comparisons of PBL heights derived from CALIPSO and ECMWF reanalysis data over China

Large bias exists in the shortwave cloud radiative effect (SWCRE) of general circulation models (GCMs), with unclear contributions from individual cloud properties. Here we present a machine‐learning approach, demonstrated using the FGOALS‐f3‐L GCM, to clarify the bias decomposition. A random‐forest model for calculating SWCRE was developed using observation and model data of cloud fraction (CFR), cloud‐solar concurrence ratio (CSC), cloud liquid/ice water paths (LWP/IWP), top of the atmosphere (TOA) upward clear‐sky solar flux (SUC), and solar zenith angle. Then, following the partial radiation perturbation method, we reveal that the global‐mean TOA SWCRE bias (in W m−2) is mainly contributed by CFR (+5.67), LWP (−5.92), CSC (+3.28), and IWP (−1.72). Regionally, the relative importance varies according to climate regimes. The large CSC contribution highlights the importance of cloud diurnal variation. The sensitivity to the observational data was discussed, emphasizing the necessity of reducing observational uncertainties for implementing effective model‐improving measures.

The Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) satellite will be launched in April of 2005, and will make continuous measurements of the Earth's atmosphere for the following three years. Retrieving the spatial and optical properties of clouds and aerosols from the CALIPSO lidar backscatter data will be confronted by a number of difficulties that are not faced in the analysis of ground-based data. Among these are the very large distance from the target, the high speed at which the satellite traverses the ground track, and the ensuing low signal-to-noise ratios that result from the mass and power restrictions imposed on space-based platforms. In this work we describe an integrated analysis scheme that employs a nested, multi-grid averaging technique designed to optimize tradeoffs between spatial resolution and signal-to-noise ratio. We present an overview of the three fundamental retrieval algorithms (boundary location, feature classification, and optical properties analysis), and illustrate their interconnections using data product examples that include feature top and base altitudes, feature type (i.e., cloud or aerosol), and layer optical depths.

Lidar investigation of temporal and vertical optical atmospheric properties will play a key role in the future for a continuous monitoring over the whole planet through world ground based networks. The EZ Lidar™, manufactured by LEOSPHERE, has been validated in several campaigns as that one in Southern Great Plains (ARM) or at Goddard Space Flight Center (NASA). An EZ LIDAR™ with cross-polariza tion capabilities was deployed in Kanpur, India in the frame of TIGER-Z campaign organized by NASA/AERONET in order to measure aerosol microphysical and optical properties in the Gange basin. In addition, 12 sun-photometers were deployed during this campaign and CALIPSO (The Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation) data were also acquired. In this work we present the results in retrieving aerosol extinction and back scattering from EZ Lidar™ measurements , and the validation of the space borne instrument CALIPSO under the satellite track. EZ Lidar™ is also coupled with the photometers to provide the measurements of the Aerosol Optical Depth over the selected region. Keywords: Pollution, Aerosol Optical Depth, Aerosol Lidar

This paper is the companion paper of Córdoba-Jabonero et al. (2021). It deals with the estimation of the longwave (LW) and net dust direct radiative effect (DRE) during the dust episode that occurred between 23 and 30 June, 2019, and coincided with a mega-heatwave. The analysis is performed at two European sites where polarized-Micro-Pulse Lidars ran continuously to retrieve the vertical distribution of the dust optical properties: Barcelona, Spain, 23–30 June, and Leipzig, Germany, 29–30 June. The radiative effect is computed with the GAME radiative transfer model separately for the fine- and coarse-mode dust. The instantaneous and daily radiative effect and radiative efficiency (DREff) are provided for the fine-mode, coarse-mode and total dust at the surface, top of the atmosphere (TOA) and in the atmosphere. The fine-mode daily LW DRE is small (< 6 % of the shortwave (SW) component) which makes the coarse-mode LW DRE the main modulator of the total dust net DRE. The coarse-mode LW DRE starts exceeding (in absolute values) the SW component in the middle of the episode which produces positive coarse-mode net DRE at both the surface and TOA. Such an unusual tendency is attributed to increasing coarse-mode size and surface temperature along the episode. This has the effect of reducing the SW cooling in Barcelona up to the point of reaching total dust net DRE positive (+0.9 W m−2) on one occasion at the surface and quasi-neutral (−0.6 W m−2) at TOA. When adding the LW component, the total dust SW radiative efficiency is reduced by a factor 1.6 at both surface (on average over the episode, the total dust net DREff is −54.1 W m−2 τ−1) and TOA (−37.3 W m−2 τ−1). A sensitivity study performed on the surface temperature and the air temperature in the dust layer, both linked to the heatwave and upon which the LW DRE strongly depends, shows that the heatwave contributed to reduce the dust net cooling effect at the surface and that it had nearly no effect at TOA. Its subsequent effect was thus to reduce the heating of the atmosphere produced by the dust particles.